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Found 25 papers, 7 papers with code
Is Foreground Prototype Sufficient? Few-Shot Medical Image Segmentation with Background-Fused Prototype
However, this paradigm is not applicable to medical images where the foreground and background share numerous visual features, necessitating a more detailed description for background.
AniGS: Animatable Gaussian Avatar from a Single Image with Inconsistent Gaussian Reconstruction
Generating animatable human avatars from a single image is essential for various digital human modeling applications.
LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning
For captioning, we finetune a large language model with the language-informative motion features to develop a strong motion captioning model.
MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling
Motion generation from discrete quantization offers many advantages over continuous regression, but at the cost of inevitable approximation errors.
Atlas Gaussians Diffusion for 3D Generation
Using the latent diffusion model has proven effective in developing novel 3D generation techniques.
An Optimization Framework to Enforce Multi-View Consistency for Texturing 3D Meshes
In particular, the third and fourth stages are iterated, with the cuts obtained in the fourth stage encouraging non-rigid alignment in the third stage to focus on regions close to the cuts.
VideoMV: Consistent Multi-View Generation Based on Large Video Generative Model
Images from video generative models are more suitable for multi-view generation because the underlying network architecture that generates them employs a temporal module to enforce frame consistency.
URHand: Universal Relightable Hands
To simplify the personalization process while retaining photorealism, we build a powerful universal relightable prior based on neural relighting from multi-view images of hands captured in a light stage with hundreds of identities.
GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors
The key to our approach is a new diffusion procedure that combines the discrete empirical data distribution and a continuous distribution induced by the quality checker.
Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs
GPUs have become the \emph{defacto} hardware devices for accelerating Deep Neural Network (DNN) inference workloads.
Video-based Visible-Infrared Person Re-Identification with Auxiliary Samples
Previous methods focus on learning from cross-modality person images in different cameras.
Word4Per: Zero-shot Composed Person Retrieval
Searching for specific person has great social benefits and security value, and it often involves a combination of visual and textual information.
Ranked #1 on
Zero-shot Composed Person Retrieval
on ITCPR dataset
(using extra training data)
Ctrl-Room: Controllable Text-to-3D Room Meshes Generation with Layout Constraints
Next, the Appearance Generation Stage employs a fine-tuned ControlNet to produce a vivid panoramic image of the room guided by the 3D scene layout and text prompt.
Text-guided Image Restoration and Semantic Enhancement for Text-to-Image Person Retrieval
To address this issue, we propose a novel TIPR framework to build fine-grained interactions and alignment between person images and the corresponding texts.
PanoContext-Former: Panoramic Total Scene Understanding with a Transformer
Panoramic image enables deeper understanding and more holistic perception of $360^\circ$ surrounding environment, which can naturally encode enriched scene context information compared to standard perspective image.
Task-aware Adaptive Learning for Cross-domain Few-shot Learning
In this paper, we first observe the dependence of task-specific parameter configuration on the target task.
PanoViT: Vision Transformer for Room Layout Estimation from a Single Panoramic Image
In this paper, we propose PanoViT, a panorama vision transformer to estimate the room layout from a single panoramic image.
Caption Feature Space Regularization for Audio Captioning
To eliminate this negative effect, in this paper, we propose a two-stage framework for audio captioning: (i) in the first stage, via the contrastive learning, we construct a proxy feature space to reduce the distances between captions correlated to the same audio, and (ii) in the second stage, the proxy feature space is utilized as additional supervision to encourage the model to be optimized in the direction that benefits all the correlated captions.
Modeling Clothing as a Separate Layer for an Animatable Human Avatar
To address these difficulties, we propose a method to build an animatable clothed body avatar with an explicit representation of the clothing on the upper body from multi-view captured videos.
TLRM: Task-level Relation Module for GNN-based Few-Shot Learning
We consider this method of measuring relation of samples only models the sample-to-sample relation, while neglects the specificity of different tasks.
Inverse Structural Design of Graphene/Boron Nitride Hybrids by Regressional GAN
A significant novelty of the proposed RGAN is that it combines the supervised and regressional convolutional neural network (CNN) with the traditional unsupervised GAN, thus overcoming the common technical barrier in the traditional GANs, which cannot generate data associated with given continuous quantitative labels.
Computational Physics Materials Science Applied Physics
MSFD:Multi-Scale Receptive Field Face Detector
We simultaneously propose an anchor assignment strategy which can cover faces with a wide range of scales to improve the recall rate of small faces and rotated faces.
Multi-hierarchical Independent Correlation Filters for Visual Tracking
For visual tracking, most of the traditional correlation filters (CF) based methods suffer from the bottleneck of feature redundancy and lack of motion information.
Deep Learning Bandgaps of Topologically Doped Graphene
Moreover, given ubiquitous existence of topologies in materials, this work will stimulate widespread interests in applying deep learning algorithms to topological design of materials crossing atomic, nano-, meso-, and macro- scales.
Materials Science Computational Physics
BodyFusion: Real-Time Capture of Human Motion and Surface Geometry Using a Single Depth Camera
To reduce the ambiguities of the non-rigid deformation parameterization on the surface graph nodes, we take advantage of the internal articulated motion prior for human performance and contribute a skeleton-embedded surface fusion (SSF) method.
